This concise book for engineering and sciences students emphasizes modern statistical methodology and data analysis. APPLIED STATISTICS FOR ENGINEERS AND SCIENTISTS is ideal for one-term courses that cover probability only to the extent that it is needed for inference. The authors emphasize application of methods to real problems, with real examples throughout. The text is designed to meet ABET standards and has been updated to reflect the most current methodology and practice.

Benefits:

Examples that use real data from industry reports and articles introduce students to real-world situations while they learn statistical concepts.

NEW! Computer output has been updated to reflect the latest technology.

NEW! The integration of the "Six Sigma Terminology" in Chapter 6 adds to the text's modern approach.

NEW! Chapter Exercises, which come at the end of the chapters, replace the Supplementary Exercises, which were previously at the beginning of the chapters.

The authors cover all the important topics concisely, giving students a solid understanding of both statistical methods and design with a problem-solving focus.

The authors emphasize modern statistical methods including quality and design of experiments to give students exposure to practical applications.

An emphasis on graphical data analysis methods is consistent with the authors' computer-integrated approach.

Practical computer pedagogy is integrated throughout the book so that learning of concepts can focus on real applications.

Numerous relevant, current exercises and examples appear throughout.

NEW! New exercises and examples, based on real data and information from published sources reinforce the practical, realistic approach that helps students relate to and understand statistical concepts better.

NEW! Discussions of stratified sampling and reliability have been added.

NEW! An update of confidence intervals for proportions reflects recent developments in improving the estimates.

Terminology. How Control Charts Work. Control Charts for Mean and Variance. Process Capability Analysis. Control Charts for Attribute Data. Supplementary Exercises. Bibliography.

7. ESTIMATION AND STATISTICAL INTERVALS.

Point Estimation. Large-Sample Confidence Intervals for a Population Mean. More Large-Sample Confidence Intervals. Small-Sample Intervals Based on a Normal Population Distribution. Intervals for µ1-µ2 Based on a Normal Population Distributions. Other Topics in Estimation (Optional). Supplementary Exercises. Bibliography.

8. TESTING STATISTICAL HYPOTHESES.

Hypotheses and Test Procedures. Tests Concerning Hypotheses About Means. Tests Concerning Hypotheses About a Categorical Population. Testing the Form of a Distribution. Further Aspects of Hypothesis Testing. Supplementary Exercises. Bibliography.

This concise book for engineering and sciences students emphasizes modern statistical methodology and data analysis. APPLIED STATISTICS FOR ENGINEERS AND SCIENTISTS is ideal for one-term courses that cover probability only to the extent that it is needed for inference. The authors emphasize application of methods to real problems, with real examples throughout. The text is designed to meet ABET standards and has been updated to reflect the most current methodology and practice.

Benefits:

Examples that use real data from industry reports and articles introduce students to real-world situations while they learn statistical concepts.

NEW! Computer output has been updated to reflect the latest technology.

NEW! The integration of the "Six Sigma Terminology" in Chapter 6 adds to the text's modern approach.

NEW! Chapter Exercises, which come at the end of the chapters, replace the Supplementary Exercises, which were previously at the beginning of the chapters.

The authors cover all the important topics concisely, giving students a solid understanding of both statistical methods and design with a problem-solving focus.

The authors emphasize modern statistical methods including quality and design of experiments to give students exposure to practical applications.

An emphasis on graphical data analysis methods is consistent with the authors' computer-integrated approach.

Practical computer pedagogy is integrated throughout the book so that learning of concepts can focus on real applications.

Numerous relevant, current exercises and examples appear throughout.

NEW! New exercises and examples, based on real data and information from published sources reinforce the practical, realistic approach that helps students relate to and understand statistical concepts better.

NEW! Discussions of stratified sampling and reliability have been added.

NEW! An update of confidence intervals for proportions reflects recent developments in improving the estimates.

Terminology. How Control Charts Work. Control Charts for Mean and Variance. Process Capability Analysis. Control Charts for Attribute Data. Supplementary Exercises. Bibliography.

7. ESTIMATION AND STATISTICAL INTERVALS.

Point Estimation. Large-Sample Confidence Intervals for a Population Mean. More Large-Sample Confidence Intervals. Small-Sample Intervals Based on a Normal Population Distribution. Intervals for µ1-µ2 Based on a Normal Population Distributions. Other Topics in Estimation (Optional). Supplementary Exercises. Bibliography.

8. TESTING STATISTICAL HYPOTHESES.

Hypotheses and Test Procedures. Tests Concerning Hypotheses About Means. Tests Concerning Hypotheses About a Categorical Population. Testing the Form of a Distribution. Further Aspects of Hypothesis Testing. Supplementary Exercises. Bibliography.